Triple

T1163712
Position Surface form Disambiguated ID Type / Status
Subject Belgrade E24551 entity
Predicate hasMunicipality P847 FINISHED
Object Zvezdara
Zvezdara is a residential and hilly municipality of Belgrade known for its large forested area and the Belgrade Observatory.
E133515 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Zvezdara | Statement: [Belgrade, hasMunicipality, Zvezdara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zvezdara
Context triple: [Belgrade, hasMunicipality, Zvezdara]
  • A. Zrenjanin
    Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat region.
  • B. Nova Gorica
    Nova Gorica is a Slovenian town on the border with Italy, known for its post-World War II development as a planned city and its close integration with the neighboring Italian town of Gorizia.
  • C. Niš
    Niš is one of the largest and oldest cities in Serbia, known as a key cultural, economic, and transportation hub in the southern part of the country.
  • D. Marić
    Marić is the Serbian family name of Mileva Marić, a pioneering physicist and mathematician known for her association with Albert Einstein.
  • E. Baščaršija
    Baščaršija is Sarajevo’s historic Ottoman-era bazaar and cultural center, known for its narrow cobbled streets, traditional shops, and iconic architecture.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Zvezdara
Triple: [Belgrade, hasMunicipality, Zvezdara]
Generated description
Zvezdara is a residential and hilly municipality of Belgrade known for its large forested area and the Belgrade Observatory.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zvezdara
Target entity description: Zvezdara is a residential and hilly municipality of Belgrade known for its large forested area and the Belgrade Observatory.
  • A. Zrenjanin
    Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat region.
  • B. Nova Gorica
    Nova Gorica is a Slovenian town on the border with Italy, known for its post-World War II development as a planned city and its close integration with the neighboring Italian town of Gorizia.
  • C. Niš
    Niš is one of the largest and oldest cities in Serbia, known as a key cultural, economic, and transportation hub in the southern part of the country.
  • D. Marić
    Marić is the Serbian family name of Mileva Marić, a pioneering physicist and mathematician known for her association with Albert Einstein.
  • E. Baščaršija
    Baščaršija is Sarajevo’s historic Ottoman-era bazaar and cultural center, known for its narrow cobbled streets, traditional shops, and iconic architecture.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a494060e148190abb42f971242c197 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bcc9dc5081908e225a485186ab12 completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac66803e0881908d2eea76dad028fa completed March 7, 2026, 5:55 p.m.
NEDg Description generation batch_69ac670b57808190bee4aa0be78ae8a1 completed March 7, 2026, 5:57 p.m.
NED2 Entity disambiguation (via description) batch_69ac67e981e88190b10ad4ab72337557 completed March 7, 2026, 6:01 p.m.
Created at: March 1, 2026, 7:45 p.m.